We investigate the hypothesis that the low-level image features used to index the trademark images can be correlated with image contents by applying a relevance feedback mechanism that evaluates the feature distributions of the images judged relevant, or not relevant, by the user, and dynamically updates both the similarity measure and query in order to better represent the user's particular information needs. Experimental results on a database of 1100 trademarks are reported.


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    Title :

    Similarity retrieval of trademark images


    Contributors:
    Ciocca, G. (author) / Schettini, R. (author)


    Publication date :

    1999-01-01


    Size :

    163779 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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